---
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: lc_cate
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# lc_cate

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3148
- Accuracy: 0.7535
- F1: 0.7694
- Precision: 0.7812
- Recall: 0.7579

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 32   | 0.2704          | 0.7415   | 0.7640 | 0.7874    | 0.7421 |
| No log        | 2.0   | 64   | 0.2764          | 0.7275   | 0.7497 | 0.7726    | 0.7282 |
| No log        | 3.0   | 96   | 0.2802          | 0.7495   | 0.7675 | 0.7859    | 0.75   |
| No log        | 4.0   | 128  | 0.2915          | 0.7435   | 0.7614 | 0.7796    | 0.7440 |
| No log        | 5.0   | 160  | 0.3044          | 0.7214   | 0.7472 | 0.7717    | 0.7242 |
| No log        | 6.0   | 192  | 0.2972          | 0.7595   | 0.7737 | 0.7881    | 0.7599 |
| No log        | 7.0   | 224  | 0.3061          | 0.7375   | 0.7626 | 0.7735    | 0.7520 |
| No log        | 8.0   | 256  | 0.3049          | 0.7615   | 0.7759 | 0.7862    | 0.7659 |
| No log        | 9.0   | 288  | 0.3073          | 0.7475   | 0.7657 | 0.7798    | 0.7520 |
| No log        | 10.0  | 320  | 0.3067          | 0.7515   | 0.7705 | 0.7856    | 0.7560 |
| No log        | 11.0  | 352  | 0.3187          | 0.7455   | 0.7647 | 0.7822    | 0.7480 |
| No log        | 12.0  | 384  | 0.3148          | 0.7535   | 0.7694 | 0.7812    | 0.7579 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1